Lead AI/ML Engineer (Platform, kubeflow)

Capital One Financial

Quick summary

Work type
On-site
Location
San Jose, CA · San Francisco, CA · McLean, VA · New York, NY
Salary
$197,300–$225,100 / yr
Posted
31 days ago

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $216k
This role $211k
$170k most similar roles pay here $270k

This role pays less than 52% of similar roles. Most pay $184,975–$246,150 — the shaded band above. At the midpoint, this role pays about $211k versus about $216k for comparable roles.

Based on 240 similar postings.

Employer

About Capital One Financial

Capital One Financial is a bank holding company specializing in credit cards, auto loans, banking, and savings products, known for its data-driven approach to consumer and commercial finance. Industry: Financial Services & Banking

Capital One Financial currently has 498 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 495 roles with salary data.

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View all roles at Capital One Financial

At a glance

TL;DR · Lead AI/ML Engineer (Platform, kubeflow)

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As a Lead AI/ML Engineer on the platform team, you will oversee and innovate in the development of scalable machine learning solutions using Kubeflow. Your primary responsibilities include designing and implementing robust ML pipelines, optimizing model deployment across Kubernetes clusters, and ensuring seamless integration with existing data infrastructure. You will work closely with cross-functional teams to address complex business challenges through advanced AI techniques. Ideal candidates possess extensive experience with Python, TensorFlow, and PyTorch, alongside expertise in cloud platforms like AWS or GCP. The role demands a deep understanding of distributed systems, containerization technologies such as Docker, and proficiency in CI/CD practices for ML workflows.

Skills

Kubeflow Python TensorFlow PyTorch CI/CD Docker Kubernetes AWS GCP Azure Git Jenkins Prometheus Grafana PostgreSQL MongoDB Scikit-learn Pandas

What you'll do

  • Design and implement scalable machine learning platforms using Kubeflow.
  • Optimize ML workflows to enhance performance and reduce computational costs.
  • Develop automated pipelines for model training, deployment, and monitoring.
  • Ensure robust data management practices for secure and efficient operations.
  • Mentor junior engineers in AI/ML best practices and technological advancements.

What we're looking for

  • Extensive experience in AI/ML engineering and Kubeflow platform.
  • Strong background in developing scalable machine learning solutions.
  • Proficiency in cloud platforms like AWS, Azure, or GCP for ML workloads.
  • Experience with CI/CD pipelines and DevOps practices for ML projects.
  • Excellent problem-solving skills and deep technical expertise in AI.

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